A Two-Stage Method for the Approximate Solution of General Multiparametric Mixed-Integer Linear Programming Problems Academic Article uri icon

abstract

  • In this work, we focus on the approximate solution of multiparametric mixed-integer linear programming (mp-MILP) problems involving uncertainty in the objective function coefficients and in the entries of the constraint matrices and vectors. A two-stage algorithmic procedure is proposed. In the first stage, the model is partially immunized against uncertainty using the worst-case oriented approach which leads to a partially robust mp-MILP model, whereas in the second stage explicit solutions of the robust model are derived by applying a suitable multiparametric programming algorithm for mp-MILP problems. Computational studies are presented, demonstrating that the proposed two-stage robust optimization/multiparametric programming procedure is computationally efficient and that it provides an upper bound on the overall solution of the general mp-MILP problem. © 2012 American Chemical Society.

author list (cited authors)

  • Wittmann-Hohlbein, M., & Pistikopoulos, E. N.

citation count

  • 19

publication date

  • June 2012